25 papers
Conformalized Large Language Models under Configuration Shift
Yuqicheng Zhu, Jialin Yu, Lin Li +7
Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs), providing prediction sets…
Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation
Nadeem Nazer, Hongkuan Zhou, Lavdim Halilaj +2
Recent vision-language models (VLMs) like CLIP have shown impressive anomaly detection performance under significant distribution shift by utilizing high-level semantic information…
GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models
Hongkuan Zhou, Tristan Rehm, Nadeem Nazer +3
Industrial inspection requires more than binary anomaly detection: a practical system should determine whether an anomaly exists, localize the defective region, identify the defect…
SCAIR: Schema-Conditioned Agentic Iterative Reasoning for Enterprise Knowledge Graphs
Prateek Chaturvedi, Yuqicheng Zhu, Hongkuan Zhou +6
Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) enables natural language interaction with structured enterprise knowledge, yet existing agentic approaches that perfor…
Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings
Yuqicheng Zhu, Nico Potyka, Bo Xiong +4
Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilisti…
KAPPS: A knowledge-based CPPS Architecture for the Circular Factory
Etienne Hoffmann, Jan-Felix Klein, Sören Weindel +7
While linear manufacturing relies on homogeneous materials and predefined process sequences, circular manufacturing reintroduces used products with heterogeneous and uncertain cond…